Efficient face emotion recognition in photos and videos
The repo contains an audio emotion detection model, facial emotion detection model, and a model that combines both these models to predict emotions from a video
A computer vision project.
Moody is a web application allowing the host of online meetings (e.g. via Zoom, Microsoft Teams or Google Meet) to collect real-time feedback of the participant's emotions.
Face emotion detection system .
Recognition of Iranian human facial emotions across four categories: Happy, Sad, Angry, and Neutral.
A Face Emotion Recognizer
Build a Face Emotion Recognition (FER) Algorithm
This project is a part of "Deep Learning + ML Engineering” curriculum as capstone projects at Almabetter School.
Super lite Flask app that can perform emotion detection
Facial Expression Recognition System using YOLOv9 & Flask. Detects 5 emotions (Angry, Happy, Natural, Sad, Surprised) from images/live camera with mAP50 of 0.731. Features a web interface with file uploads, real-time processing, & emoji feedback. Built with Python, OpenCV, Flask, HTML/CSS/JS. Ideal for HCI & emotion analysis.
Face-Emotion-Recognition using a model trained over MobileNet with an accuracy of 70%
Face Emotion Recognition using FER2013 dataset. Test accuracy: 69.35%
Face emotion recognition technology detects emotions and mood patterns invoked in human faces. This technology is used as a sentiment analysis tool to identify the six universal expressions, namely, happiness, sadness, anger, surprise, fear and disgust. Identifying facial expressions has a wide range of applications in human social interaction d…
This web app uses face-api to detect face using webcam live video feed.
Building and testing several models for real-time facial emotion recognition.
A from-scratch SOTA PyTorch implementation of the Inception-ResNet-V2 model designed by Szegedy et. al., adapted for Face Emotion Recognition (FER), with custom dataset support.
Face Emotion Detection using CNN
Real time emotion recognition, using OpenCV and haarcascade algorithm for face detection from the video source, then I've done emotion recognition using a model trained on FER-2013 dataset with Tensorflow. and also as an other solution, I used DeepFace package for emotion recognition as a prefabricated solution.
Build a full stack application with object-face-emotion recognition
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